Araştırma Makalesi
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Kısa Dönemli Hidrolojik Tahmin Sistemi Uygulaması

Yıl 2021, Cilt: 7 Sayı: 2, 338 - 353, 25.07.2021
https://doi.org/10.21324/dacd.863585

Öz

Bu çalışmanın amacı kar erimesinin etkili olduğu dağlık memba havzaları için kısa dönemli akım tahmin sisteminin geliştirilmesidir. Çalışma alanları olarak seçilen dağlık Fırat ve Seyhan Havzaları, yüksek su potansiyeli, bu potansiyeli besleyen kar erimeleri, mansapta büyük ve önemli su yapılarının bulunması ile ön plana çıkmaktadırlar. Yağış-akış ilişkisinin simülasyonu için dağlık bölge uygulamalarında literatürde yaygın olarak kullanılan HBV modeli seçilmiştir. Sayısal Hava Tahmin (SHT) verisi olarak Mesoscale Model 5 (MM5) ve Weather Research and Forecast (WRF) model sonuçları kullanılmıştır. Hidrolojik model parametrelerinin gözlenen yağış, sıcaklık ve akım verileriyle kalibrasyon/doğrulama işleminin yapılmasının ardından, analizleri yapılan SHT verilerinin girdi olarak kullanılması ile 1 ve 2 günlük akım tahminleri elde edilmiştir. İleriye dönük akım tahminleri Delft-FEWS platformunda kapalı döngü şeklinde çalıştırılarak, geçmiş dönem tahmin simülasyonları gerçekleştirilmiş ve akım gözlemleri ile kıyaslanarak performans değerlendirmesi yapılmıştır. Elde edilen sonuçlar havzaların akış aşağısında bulunan su yapılarının daha verimli işletilmesine ve böylece ülke ekonomisine katkı sağlayabilecektir.

Destekleyen Kurum

TÜBİTAK

Proje Numarası

113Y075

Teşekkür

Bu çalışma 113Y075 numaralı TÜBİTAK projesi ve ES1404 aksiyon numaralı COST projesi kapsamında desteklenmiştir. Veri paylaşımı için Devlet Su İşleri (DSİ) ve Meteoroloji Genel Müdürlüğüne (MGM) teşekkür ederiz.

Kaynakça

  • Albostan A., Önöz B., (2010), Seasonality measurement of low-flows: Mid-Euphrates Basin example, 9th Advances in Civil Engineering Conference (ACE 2010)’in İçinde, September 27-30, Karadeniz Technical University, Trabzon, Turkey.
  • Anderson M.L., Chen Z.Q., Kavvas M.L., Feldman A., (2002), Coupling HEC-HMS with atmospheric models for prediction of watershed runoff, Journal of Hydrologic Engineering, 7(4), 312-318.
  • Belair S., Roch M., Leduc A.M., Vaillancourt P.A., Laroche S., Mailhot J., (2009), Medium-range quantitative precipitation forecasts from Canada’s new 33-km deterministic global operational system, Weather and Forecasting, 24(3), 690-708.
  • Bergström S., (1976), Development and application of a conceptual runoff model for Scandinavian catchments, Doktora Tezi, SMHI Reports RHO No. 7, Norrköping.
  • Bergström S., Lindström G., (2015), Interpretation of runoff processes in hydrological modelling—experience from the HBV approach, Hydrological Processes, 29(16), 3535-3545.
  • Buhan S., Kucuk D., Cinar M.S., Güvengir U., Demirci T., Yilmaz Y., ...Yildirim M.U., (2019), A Scalable River Flow Forecast and Basin Optimization System for Hydropower Plants, IEEE Transactions on Sustainable Energy, doi: 10.1109/TSTE.2019.2952450.
  • Casati B., Wilson L.J., Stephenson D.B., Nurmi P., Ghelli A., Pocernich M., ...Mason S., (2008), Forecast verification: current status and future directions, Meteorological Applications: A journal of forecasting, practical applications, training techniques and modelling, 15(1), 3-18.
  • Cuo L., Pagano T.C., Wang Q.J., (2011), A review of quantitative precipitation forecasts and their use in short-to medium-range streamflow forecasting, Journal of hydrometeorology, 12(5), 713-728.
  • Çakmak Ö., Temiz Ö., Baran T., (2010), Dicle Havzası Billoris AGİ yıllık ve aylık akımların stokastik modellenmesi, VI. Ulusal Hidroloji Kongresi, 22–24 Eylül, Pamukkale Üniversitesi, Denizli.
  • Durai V.R., Bhradwaj R., (2014), Evaluation of statistical bias correction methods for numerical weather prediction model forecasts of maximum and minimum temperatures, Natural Hazards, 73(3), 1229-1254.
  • Ebert E.E., Damrath U., Wergen W., Baldwin M.E., (2003), The WGNE assessment of short-term quantitative precipitation forecasts, Bulletin of the American Meteorological Society, 84(4), 481-492.
  • El Khalki E.M., Tramblay Y., Amengual A., Homar V., Romero R., Saidi M.E.M., Alaouri M., (2020), Validation of the AROME, ALADIN and WRF Meteorological Models for Flood Forecasting in Morocco, Water, 12(2), 437, doi: 10.3390/w12020437.
  • Finger D., Vis M., Huss M., Seibert J., (2015), The value of multiple data set calibration versus model complexity for improving the performance of hydrological models in mountain catchments, Water Resources Research, 51, 1939-1958.
  • Gallus Jr W.A., Segal M., (2001), Impact of improved initialization of mesoscale features on convective system rainfall in 10-km Eta simulations, Weather and Forecasting, 16(6), 680-696.
  • Ghajarnia N., Liaghat A., Arasteh P.D., (2015), Comparison and evaluation of high resolution precipitation estimation products in Urmia Basin-Iran, Atmospheric Research, 158, 50-65.
  • Givati A., Gochis D., Rummler T., Kunstmann H., (2016), Comparing one-way and two-way coupled hydrometeorological forecasting systems for flood forecasting in the Mediterranean region, Hydrology, 3(2), 19, doi: 10.3390/hydrology3020019.
  • Habets F., LeMoigne P., Noilhan J., (2004), On the utility of operational precipitation forecasts to served as input for streamflow forecasting, Journal of Hydrology, 293(1-4), 270-288.
  • Hamill T.M., (1999), Hypothesis tests for evaluating numerical precipitation forecasts, Weather and Forecasting, 14(2), 155-167.
  • Immerzeel W.W., Lutz A.F., Andrade M., Bahl A., Biemans H., Bolch T., ... Baillie J.E.M., (2020), Importance and vulnerability of the world’s water towers, Nature, 577(7790), 364-369.
  • Johansson B., Caves R., Ferguson R., Turpin O., (2001), Using remote sensing data to update the simulated snow pack of the HBV runoff model, IAHS PUBLICATION, 595-597.
  • Jolliffe I.T., Stephenson D.B. (Eds.), (2012), Forecast verification: a practitioner's guide in atmospheric science, John Wiley and Sons.
  • Jónsdóttir J.F., Sórarinsson J.S., (2004), Comparison of HBV models driven with weather station data and with MM5 meteorological model data, Orkustofnun Hydrological Services, Report No. OS-2004/017.
  • Kunstmann H., Stadler C., (2005), High resolution distributed atmospheric-hydrological modelling for Alpine catchments, Journal of hydrology, 314(1-4), 105-124.
  • Mailhot J., Bélair S., Lefaivre L., Bilodeau B., Desgagné M., Girard C., ...Qaddouri A., (2006), The 15‐km version of the Canadian regional forecast system, Atmosphere-Ocean, 44(2), 133-149.
  • Martinec, J. (1975) Snowmelt-Runoff Model for stream flow forecasts. Nordic Hydrology, 6(3), 145-154.
  • Martinec J., Rango A., Roberts R., (1998), The Snowmelt Runoff Model (SRM) User’s Manual, Geographica Bernensia, P29, Department of Geography, University of Berne, Berne, Switzerland.
  • Özdemir O., (2001), Çok amaçlı ardışık barajların işletilmesi, Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 16(2), 53-61.
  • Pangali Sharma T.P., Zhang J., Khanal N.R., Prodhan F.A., Paudel B., Shi L., Nepal N., (2020), Assimilation of Snowmelt Runoff Model (SRM) using Satellite Remote Sensing Data in Budhi Gandaki River Basin, Nepal, Remote Sensing, (12), 1951, doi: 10.3390/rs12121951.
  • Rossa A., Liechti K., Zappa M., Bruen M., Germann U., Haase G., ... Krahe P., (2011), The COST 731 Action: A review on uncertainty propagation in advanced hydro-meteorological forecast systems, Atmospheric Research, 100(2-3), 150-167.
  • Selek B., Yazici D.D., Aksu H., Özdemir A.D., (2016), Seyhan Dam, Turkey, and climate change adaptation strategies, In Increasing Resilience to Climate Variability and Change (pp. 205-231). Springer, Singapore.
  • Sen O.L., Unal A., Bozkurt D., Kindap T., (2011), Temporal changes in the Euphrates and Tigris discharges and teleconnections, Environmental Research Letters, 6(2), 024012, doi:10.1088/1748-9326/6/2/024012.
  • Sharifi E., Steinacker R., Saghafian B., (2018), Multi time-scale evaluation of high-resolution satellite-based precipitation products over northeast of Austria, Atmospheric Research, 206, 46-63.
  • Shirali E., Shahbazi A.N., Fathian H., Zohrabi N., Hassan E.M., (2020), Evaluation of WRF and artificial intelligence models in short-term rainfall, temperature and flood forecast (case study), Journal of Earth System Science, 129(1), 1-16.
  • SMHI, (1996), IHMS: Integrated hydrological modeling system manual, Version 4.0. Swedish Meteorological and Hydrological Institute, Norrköping, Sweden.
  • Shrestha D.L., Robertson D.E., Wang Q.J., Pagano T.C., Hapuarachchi, H.A.P., (2013), Evaluation of numerical weather prediction model precipitation forecasts for short-term streamflow forecasting purpose, Hydrology and Earth System Sciences, 17(5), 1913. doi:10.5194/hess-17-1913-2013.
  • Şensoy A., Uysal G., (2012), The value of snow depletion forecasting methods towards operational snowmelt runoff estimation using MODIS and Numerical Weather Prediction Data, Water Resources Management, 26(12), 3415-3440.
  • Şorman A.A., Şensoy A. Tekeli A.E., Şorman A.Ü., Akyürek, Z., (2009), Modelling and forecasting snowmelt runoff process using the HBV model in the eastern part of Turkey, Hydrological Processes: An International Journal, 23(7), 1031-1040.
  • Şorman A.A., Uysal G., Şensoy A., (2019), Probabilistic snow cover and ensemble streamflow estimations in the Upper Euphrates Basin, Journal of Hydrology and Hydromechanics, 67(1), 82-92, doi: 10.2478/johh-2018-0025.
  • Tahir A.A., Chevallier, P., Arnaud, Y., Neppel, L., Ahmad, B., (2011), Modeling snowmelt-runoff under climate scenarios in the Hunza River Basin, Karakoram Range, Northern Pakistan, Journal of Hydrology, 409, 104–117.
  • Taşdemir G., (2009), Uzaktan algılama ve Coğrafi Bilgi Sistemlerinin birlikte kullanılması ile kar erimesi akış hidrografının benzetimi (Sarız Çayı Havzası örneği), Yüksek Lisans Tezi, Gazi Üniversitesi, Fen Bilimleri Enstitüsü, Ankara.
  • te Linde A.H., Aerts J.C.J.H., Hurkmans R.T.W.L., Eberle M., (2008), Comparing model performance of two rainfall-runoff models in the Rhine basin using different atmospheric forcing data sets, Hydrology and Earth System Sciences, 12, 943-957.
  • URL-1, (2020), https://www.mmm.ucar.edu/weather-research-and-forecasting-model, [Erişim 15 Kasım 2020].
  • Uysal G., Şensoy A., Şorman, A.A., (2016), Improving daily streamflow forecasts in mountainous Upper Euphrates basin by multi-layer perceptron model with satellite snow products, Journal of Hydrology, 543, 630-650.
  • Werner M., Schellekens J., Gijsbers P., van Dijk M., van den Akker O., Heynert K., (2013), The Delft-FEWS flow forecasting system, Environmental Modelling & Software, 40, 65-77.
  • WMO, (1986), Intercomparison of models of snowmelt runoff, Publication No. 646, Operational Hydrology Report No. 23, World Meteorological Organization, Geneva, Switzerland.

Application of a Short-Term Hydrological Forecast System

Yıl 2021, Cilt: 7 Sayı: 2, 338 - 353, 25.07.2021
https://doi.org/10.21324/dacd.863585

Öz

This study aims to deploy a short term hydrological forecast system in snow dominated mountainous basins. The headwaters of Euphrates and Seyhan Basins, selected as study areas, stand out with their high water potential, snow melt feeding this potential and the presence of large and important water structures in the downstream. For the simulation of precipitation-runoff relationship, HBV model, a widely used model in the literature especially for mountainous regions, is utilized. Mesoscale Model 5 (MM5) and Weather Research and Forecast (WRF) model results are preferred as Numerical Weather Prediction (NWP) data. After calibration/validation of hydrological model parameters with observed precipitation, temperature and flow data, 1- and 2-day flow estimates are obtained using the analyzed NWP data as input. Hindcast simulations for the past period are implemented with a closed-loop structure on the Delft-FEWS platform, and performance evaluation is conducted by comparing them with streamflow observations. The results obtained may contribute to the more efficient operation of water structures located downstream of the basins and thus to the national economy.

Proje Numarası

113Y075

Kaynakça

  • Albostan A., Önöz B., (2010), Seasonality measurement of low-flows: Mid-Euphrates Basin example, 9th Advances in Civil Engineering Conference (ACE 2010)’in İçinde, September 27-30, Karadeniz Technical University, Trabzon, Turkey.
  • Anderson M.L., Chen Z.Q., Kavvas M.L., Feldman A., (2002), Coupling HEC-HMS with atmospheric models for prediction of watershed runoff, Journal of Hydrologic Engineering, 7(4), 312-318.
  • Belair S., Roch M., Leduc A.M., Vaillancourt P.A., Laroche S., Mailhot J., (2009), Medium-range quantitative precipitation forecasts from Canada’s new 33-km deterministic global operational system, Weather and Forecasting, 24(3), 690-708.
  • Bergström S., (1976), Development and application of a conceptual runoff model for Scandinavian catchments, Doktora Tezi, SMHI Reports RHO No. 7, Norrköping.
  • Bergström S., Lindström G., (2015), Interpretation of runoff processes in hydrological modelling—experience from the HBV approach, Hydrological Processes, 29(16), 3535-3545.
  • Buhan S., Kucuk D., Cinar M.S., Güvengir U., Demirci T., Yilmaz Y., ...Yildirim M.U., (2019), A Scalable River Flow Forecast and Basin Optimization System for Hydropower Plants, IEEE Transactions on Sustainable Energy, doi: 10.1109/TSTE.2019.2952450.
  • Casati B., Wilson L.J., Stephenson D.B., Nurmi P., Ghelli A., Pocernich M., ...Mason S., (2008), Forecast verification: current status and future directions, Meteorological Applications: A journal of forecasting, practical applications, training techniques and modelling, 15(1), 3-18.
  • Cuo L., Pagano T.C., Wang Q.J., (2011), A review of quantitative precipitation forecasts and their use in short-to medium-range streamflow forecasting, Journal of hydrometeorology, 12(5), 713-728.
  • Çakmak Ö., Temiz Ö., Baran T., (2010), Dicle Havzası Billoris AGİ yıllık ve aylık akımların stokastik modellenmesi, VI. Ulusal Hidroloji Kongresi, 22–24 Eylül, Pamukkale Üniversitesi, Denizli.
  • Durai V.R., Bhradwaj R., (2014), Evaluation of statistical bias correction methods for numerical weather prediction model forecasts of maximum and minimum temperatures, Natural Hazards, 73(3), 1229-1254.
  • Ebert E.E., Damrath U., Wergen W., Baldwin M.E., (2003), The WGNE assessment of short-term quantitative precipitation forecasts, Bulletin of the American Meteorological Society, 84(4), 481-492.
  • El Khalki E.M., Tramblay Y., Amengual A., Homar V., Romero R., Saidi M.E.M., Alaouri M., (2020), Validation of the AROME, ALADIN and WRF Meteorological Models for Flood Forecasting in Morocco, Water, 12(2), 437, doi: 10.3390/w12020437.
  • Finger D., Vis M., Huss M., Seibert J., (2015), The value of multiple data set calibration versus model complexity for improving the performance of hydrological models in mountain catchments, Water Resources Research, 51, 1939-1958.
  • Gallus Jr W.A., Segal M., (2001), Impact of improved initialization of mesoscale features on convective system rainfall in 10-km Eta simulations, Weather and Forecasting, 16(6), 680-696.
  • Ghajarnia N., Liaghat A., Arasteh P.D., (2015), Comparison and evaluation of high resolution precipitation estimation products in Urmia Basin-Iran, Atmospheric Research, 158, 50-65.
  • Givati A., Gochis D., Rummler T., Kunstmann H., (2016), Comparing one-way and two-way coupled hydrometeorological forecasting systems for flood forecasting in the Mediterranean region, Hydrology, 3(2), 19, doi: 10.3390/hydrology3020019.
  • Habets F., LeMoigne P., Noilhan J., (2004), On the utility of operational precipitation forecasts to served as input for streamflow forecasting, Journal of Hydrology, 293(1-4), 270-288.
  • Hamill T.M., (1999), Hypothesis tests for evaluating numerical precipitation forecasts, Weather and Forecasting, 14(2), 155-167.
  • Immerzeel W.W., Lutz A.F., Andrade M., Bahl A., Biemans H., Bolch T., ... Baillie J.E.M., (2020), Importance and vulnerability of the world’s water towers, Nature, 577(7790), 364-369.
  • Johansson B., Caves R., Ferguson R., Turpin O., (2001), Using remote sensing data to update the simulated snow pack of the HBV runoff model, IAHS PUBLICATION, 595-597.
  • Jolliffe I.T., Stephenson D.B. (Eds.), (2012), Forecast verification: a practitioner's guide in atmospheric science, John Wiley and Sons.
  • Jónsdóttir J.F., Sórarinsson J.S., (2004), Comparison of HBV models driven with weather station data and with MM5 meteorological model data, Orkustofnun Hydrological Services, Report No. OS-2004/017.
  • Kunstmann H., Stadler C., (2005), High resolution distributed atmospheric-hydrological modelling for Alpine catchments, Journal of hydrology, 314(1-4), 105-124.
  • Mailhot J., Bélair S., Lefaivre L., Bilodeau B., Desgagné M., Girard C., ...Qaddouri A., (2006), The 15‐km version of the Canadian regional forecast system, Atmosphere-Ocean, 44(2), 133-149.
  • Martinec, J. (1975) Snowmelt-Runoff Model for stream flow forecasts. Nordic Hydrology, 6(3), 145-154.
  • Martinec J., Rango A., Roberts R., (1998), The Snowmelt Runoff Model (SRM) User’s Manual, Geographica Bernensia, P29, Department of Geography, University of Berne, Berne, Switzerland.
  • Özdemir O., (2001), Çok amaçlı ardışık barajların işletilmesi, Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 16(2), 53-61.
  • Pangali Sharma T.P., Zhang J., Khanal N.R., Prodhan F.A., Paudel B., Shi L., Nepal N., (2020), Assimilation of Snowmelt Runoff Model (SRM) using Satellite Remote Sensing Data in Budhi Gandaki River Basin, Nepal, Remote Sensing, (12), 1951, doi: 10.3390/rs12121951.
  • Rossa A., Liechti K., Zappa M., Bruen M., Germann U., Haase G., ... Krahe P., (2011), The COST 731 Action: A review on uncertainty propagation in advanced hydro-meteorological forecast systems, Atmospheric Research, 100(2-3), 150-167.
  • Selek B., Yazici D.D., Aksu H., Özdemir A.D., (2016), Seyhan Dam, Turkey, and climate change adaptation strategies, In Increasing Resilience to Climate Variability and Change (pp. 205-231). Springer, Singapore.
  • Sen O.L., Unal A., Bozkurt D., Kindap T., (2011), Temporal changes in the Euphrates and Tigris discharges and teleconnections, Environmental Research Letters, 6(2), 024012, doi:10.1088/1748-9326/6/2/024012.
  • Sharifi E., Steinacker R., Saghafian B., (2018), Multi time-scale evaluation of high-resolution satellite-based precipitation products over northeast of Austria, Atmospheric Research, 206, 46-63.
  • Shirali E., Shahbazi A.N., Fathian H., Zohrabi N., Hassan E.M., (2020), Evaluation of WRF and artificial intelligence models in short-term rainfall, temperature and flood forecast (case study), Journal of Earth System Science, 129(1), 1-16.
  • SMHI, (1996), IHMS: Integrated hydrological modeling system manual, Version 4.0. Swedish Meteorological and Hydrological Institute, Norrköping, Sweden.
  • Shrestha D.L., Robertson D.E., Wang Q.J., Pagano T.C., Hapuarachchi, H.A.P., (2013), Evaluation of numerical weather prediction model precipitation forecasts for short-term streamflow forecasting purpose, Hydrology and Earth System Sciences, 17(5), 1913. doi:10.5194/hess-17-1913-2013.
  • Şensoy A., Uysal G., (2012), The value of snow depletion forecasting methods towards operational snowmelt runoff estimation using MODIS and Numerical Weather Prediction Data, Water Resources Management, 26(12), 3415-3440.
  • Şorman A.A., Şensoy A. Tekeli A.E., Şorman A.Ü., Akyürek, Z., (2009), Modelling and forecasting snowmelt runoff process using the HBV model in the eastern part of Turkey, Hydrological Processes: An International Journal, 23(7), 1031-1040.
  • Şorman A.A., Uysal G., Şensoy A., (2019), Probabilistic snow cover and ensemble streamflow estimations in the Upper Euphrates Basin, Journal of Hydrology and Hydromechanics, 67(1), 82-92, doi: 10.2478/johh-2018-0025.
  • Tahir A.A., Chevallier, P., Arnaud, Y., Neppel, L., Ahmad, B., (2011), Modeling snowmelt-runoff under climate scenarios in the Hunza River Basin, Karakoram Range, Northern Pakistan, Journal of Hydrology, 409, 104–117.
  • Taşdemir G., (2009), Uzaktan algılama ve Coğrafi Bilgi Sistemlerinin birlikte kullanılması ile kar erimesi akış hidrografının benzetimi (Sarız Çayı Havzası örneği), Yüksek Lisans Tezi, Gazi Üniversitesi, Fen Bilimleri Enstitüsü, Ankara.
  • te Linde A.H., Aerts J.C.J.H., Hurkmans R.T.W.L., Eberle M., (2008), Comparing model performance of two rainfall-runoff models in the Rhine basin using different atmospheric forcing data sets, Hydrology and Earth System Sciences, 12, 943-957.
  • URL-1, (2020), https://www.mmm.ucar.edu/weather-research-and-forecasting-model, [Erişim 15 Kasım 2020].
  • Uysal G., Şensoy A., Şorman, A.A., (2016), Improving daily streamflow forecasts in mountainous Upper Euphrates basin by multi-layer perceptron model with satellite snow products, Journal of Hydrology, 543, 630-650.
  • Werner M., Schellekens J., Gijsbers P., van Dijk M., van den Akker O., Heynert K., (2013), The Delft-FEWS flow forecasting system, Environmental Modelling & Software, 40, 65-77.
  • WMO, (1986), Intercomparison of models of snowmelt runoff, Publication No. 646, Operational Hydrology Report No. 23, World Meteorological Organization, Geneva, Switzerland.
Toplam 45 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Mühendislik
Bölüm Araştırma Makalesi
Yazarlar

Gökçen Uysal 0000-0003-0445-060X

Aynur Sensoy 0000-0003-3004-4912

Arda Şorman 0000-0003-3143-7793

Mustafa Cansaran Ertaş 0000-0002-6376-5516

Proje Numarası 113Y075
Yayımlanma Tarihi 25 Temmuz 2021
Gönderilme Tarihi 19 Ocak 2021
Kabul Tarihi 31 Mayıs 2021
Yayımlandığı Sayı Yıl 2021Cilt: 7 Sayı: 2

Kaynak Göster

APA Uysal, G., Sensoy, A., Şorman, A., Ertaş, M. C. (2021). Kısa Dönemli Hidrolojik Tahmin Sistemi Uygulaması. Doğal Afetler Ve Çevre Dergisi, 7(2), 338-353. https://doi.org/10.21324/dacd.863585
AMA Uysal G, Sensoy A, Şorman A, Ertaş MC. Kısa Dönemli Hidrolojik Tahmin Sistemi Uygulaması. Doğ Afet Çev Derg. Temmuz 2021;7(2):338-353. doi:10.21324/dacd.863585
Chicago Uysal, Gökçen, Aynur Sensoy, Arda Şorman, ve Mustafa Cansaran Ertaş. “Kısa Dönemli Hidrolojik Tahmin Sistemi Uygulaması”. Doğal Afetler Ve Çevre Dergisi 7, sy. 2 (Temmuz 2021): 338-53. https://doi.org/10.21324/dacd.863585.
EndNote Uysal G, Sensoy A, Şorman A, Ertaş MC (01 Temmuz 2021) Kısa Dönemli Hidrolojik Tahmin Sistemi Uygulaması. Doğal Afetler ve Çevre Dergisi 7 2 338–353.
IEEE G. Uysal, A. Sensoy, A. Şorman, ve M. C. Ertaş, “Kısa Dönemli Hidrolojik Tahmin Sistemi Uygulaması”, Doğ Afet Çev Derg, c. 7, sy. 2, ss. 338–353, 2021, doi: 10.21324/dacd.863585.
ISNAD Uysal, Gökçen vd. “Kısa Dönemli Hidrolojik Tahmin Sistemi Uygulaması”. Doğal Afetler ve Çevre Dergisi 7/2 (Temmuz 2021), 338-353. https://doi.org/10.21324/dacd.863585.
JAMA Uysal G, Sensoy A, Şorman A, Ertaş MC. Kısa Dönemli Hidrolojik Tahmin Sistemi Uygulaması. Doğ Afet Çev Derg. 2021;7:338–353.
MLA Uysal, Gökçen vd. “Kısa Dönemli Hidrolojik Tahmin Sistemi Uygulaması”. Doğal Afetler Ve Çevre Dergisi, c. 7, sy. 2, 2021, ss. 338-53, doi:10.21324/dacd.863585.
Vancouver Uysal G, Sensoy A, Şorman A, Ertaş MC. Kısa Dönemli Hidrolojik Tahmin Sistemi Uygulaması. Doğ Afet Çev Derg. 2021;7(2):338-53.

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